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The cis-regulatory logic of the mammalian photoreceptor transcriptional network.

Hsiau TH, Diaconu C, Myers CA, Lee J, Cepko CL, Corbo JC - PLoS ONE (2007)

Bottom Line: Examination of these CREs permitted the definition of a simple cis-regulatory grammar rule associated with high-level expression.When fused to fluorescent reporters, these evolved CREs drove strong, photoreceptor-specific expression in vivo.This study represents the first systematic identification and in vivo validation of CREs in a mammalian neuronal cell type and lays the groundwork for a systems biology of photoreceptor transcriptional regulation.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, United States of America.

ABSTRACT
The photoreceptor cells of the retina are subject to a greater number of genetic diseases than any other cell type in the human body. The majority of more than 120 cloned human blindness genes are highly expressed in photoreceptors. In order to establish an integrative framework in which to understand these diseases, we have undertaken an experimental and computational analysis of the network controlled by the mammalian photoreceptor transcription factors, Crx, Nrl, and Nr2e3. Using microarray and in situ hybridization datasets we have produced a model of this network which contains over 600 genes, including numerous retinal disease loci as well as previously uncharacterized photoreceptor transcription factors. To elucidate the connectivity of this network, we devised a computational algorithm to identify the photoreceptor-specific cis-regulatory elements (CREs) mediating the interactions between these transcription factors and their target genes. In vivo validation of our computational predictions resulted in the discovery of 19 novel photoreceptor-specific CREs near retinal disease genes. Examination of these CREs permitted the definition of a simple cis-regulatory grammar rule associated with high-level expression. To test the generality of this rule, we used an expanded form of it as a selection filter to evolve photoreceptor CREs from random DNA sequences in silico. When fused to fluorescent reporters, these evolved CREs drove strong, photoreceptor-specific expression in vivo. This study represents the first systematic identification and in vivo validation of CREs in a mammalian neuronal cell type and lays the groundwork for a systems biology of photoreceptor transcriptional regulation.

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Retinal disease genes in the photoreceptor network.This figure is a manually curated list of all retinal disease genes which are known or are likely to have a photoreceptor-enriched expression pattern. Those gene symbols which differ between mouse and human are marked with a single asterisk, and the human equivalents are given here: Cngb1 = CNGB1; Gpr98 = USH2C; Grk1 = RHOK; Gucy2e = GUCY2D; Prom1 = PROML1; Rgs9bp = R9AP; Rp1h = RP1; Ush1g = SANS. ‘Known CRE’ indicates the location of published photoreceptor CREs which have experimental support (references are given in MATERIALS AND METHODS). Annotations in this column such as ‘6.5 Kb 5’’ means the tested CRE contained the first 6.5 Kb upstream of the TSS. Known CREs predicted by our algorithm are highlighted in light green. ‘Predicted CRE(s)’ lists candidate CREs predicted by our algorithm which lie within +/− 15 Kb of the TSS. In some cases, two locations are given which represent that CRE prediction closest to the TSS and that with the highest score. Only one location is given when they are the same. Experimentally tested CREs are highlighted in red. The CREs tested for Crx and Elovl4 lie more than 15 Kb downstream of the TSS. The CRE tested for Tulp1 scores below the cutoff threshold of 200. This CRE was selected for testing during the early phases of this project using an earlier version of PhastCons with which it scored above threshold. A third predicted CRE location is given for Opn1mw which corresponds to the locus control region. ‘CRE strength’ indicates the estimated strength of the indicated CRE as tested by electroporation (see Fig. S2). The last four columns of the table show the wild-type-to-mutant ratios of the averaged microarray scores for the given gene. Dark green = downregulated under high stringency (as described in MATERIALS AND METHODS); light green = downregulated under low stringency; red = upregulated under high stringency; orange = upregulated under low stringency. A dash indicates that the gene was not significantly altered in the given mutant. ‘NA’ indicates that this gene is not represented on the Affymetrix Mouse 430 2.0 microarray.
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pone-0000643-g002: Retinal disease genes in the photoreceptor network.This figure is a manually curated list of all retinal disease genes which are known or are likely to have a photoreceptor-enriched expression pattern. Those gene symbols which differ between mouse and human are marked with a single asterisk, and the human equivalents are given here: Cngb1 = CNGB1; Gpr98 = USH2C; Grk1 = RHOK; Gucy2e = GUCY2D; Prom1 = PROML1; Rgs9bp = R9AP; Rp1h = RP1; Ush1g = SANS. ‘Known CRE’ indicates the location of published photoreceptor CREs which have experimental support (references are given in MATERIALS AND METHODS). Annotations in this column such as ‘6.5 Kb 5’’ means the tested CRE contained the first 6.5 Kb upstream of the TSS. Known CREs predicted by our algorithm are highlighted in light green. ‘Predicted CRE(s)’ lists candidate CREs predicted by our algorithm which lie within +/− 15 Kb of the TSS. In some cases, two locations are given which represent that CRE prediction closest to the TSS and that with the highest score. Only one location is given when they are the same. Experimentally tested CREs are highlighted in red. The CREs tested for Crx and Elovl4 lie more than 15 Kb downstream of the TSS. The CRE tested for Tulp1 scores below the cutoff threshold of 200. This CRE was selected for testing during the early phases of this project using an earlier version of PhastCons with which it scored above threshold. A third predicted CRE location is given for Opn1mw which corresponds to the locus control region. ‘CRE strength’ indicates the estimated strength of the indicated CRE as tested by electroporation (see Fig. S2). The last four columns of the table show the wild-type-to-mutant ratios of the averaged microarray scores for the given gene. Dark green = downregulated under high stringency (as described in MATERIALS AND METHODS); light green = downregulated under low stringency; red = upregulated under high stringency; orange = upregulated under low stringency. A dash indicates that the gene was not significantly altered in the given mutant. ‘NA’ indicates that this gene is not represented on the Affymetrix Mouse 430 2.0 microarray.

Mentions: Given the remarkable genetic heterogeneity of human retinal disease, we wished to determine the extent to which the causative genes are regulated by Crx, Nrl, and Nr2e3. A set of 58 mouse orthologs of human retinal disease genes from the Retnet database were manually curated (Fig. 2). This set is meant to encompass all disease genes with known or probable photoreceptor-enriched patterns of expression based on analysis of the literature. 89% (50/56) of those disease genes for which microarray data were available were dysregulated to some extent in at least one of the four mutant backgrounds. This finding suggests that the majority of known human retinal disease genes expressed in photoreceptors is under the transcriptional control of Crx, Nrl, and/or Nr2e3.


The cis-regulatory logic of the mammalian photoreceptor transcriptional network.

Hsiau TH, Diaconu C, Myers CA, Lee J, Cepko CL, Corbo JC - PLoS ONE (2007)

Retinal disease genes in the photoreceptor network.This figure is a manually curated list of all retinal disease genes which are known or are likely to have a photoreceptor-enriched expression pattern. Those gene symbols which differ between mouse and human are marked with a single asterisk, and the human equivalents are given here: Cngb1 = CNGB1; Gpr98 = USH2C; Grk1 = RHOK; Gucy2e = GUCY2D; Prom1 = PROML1; Rgs9bp = R9AP; Rp1h = RP1; Ush1g = SANS. ‘Known CRE’ indicates the location of published photoreceptor CREs which have experimental support (references are given in MATERIALS AND METHODS). Annotations in this column such as ‘6.5 Kb 5’’ means the tested CRE contained the first 6.5 Kb upstream of the TSS. Known CREs predicted by our algorithm are highlighted in light green. ‘Predicted CRE(s)’ lists candidate CREs predicted by our algorithm which lie within +/− 15 Kb of the TSS. In some cases, two locations are given which represent that CRE prediction closest to the TSS and that with the highest score. Only one location is given when they are the same. Experimentally tested CREs are highlighted in red. The CREs tested for Crx and Elovl4 lie more than 15 Kb downstream of the TSS. The CRE tested for Tulp1 scores below the cutoff threshold of 200. This CRE was selected for testing during the early phases of this project using an earlier version of PhastCons with which it scored above threshold. A third predicted CRE location is given for Opn1mw which corresponds to the locus control region. ‘CRE strength’ indicates the estimated strength of the indicated CRE as tested by electroporation (see Fig. S2). The last four columns of the table show the wild-type-to-mutant ratios of the averaged microarray scores for the given gene. Dark green = downregulated under high stringency (as described in MATERIALS AND METHODS); light green = downregulated under low stringency; red = upregulated under high stringency; orange = upregulated under low stringency. A dash indicates that the gene was not significantly altered in the given mutant. ‘NA’ indicates that this gene is not represented on the Affymetrix Mouse 430 2.0 microarray.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC1916400&req=5

pone-0000643-g002: Retinal disease genes in the photoreceptor network.This figure is a manually curated list of all retinal disease genes which are known or are likely to have a photoreceptor-enriched expression pattern. Those gene symbols which differ between mouse and human are marked with a single asterisk, and the human equivalents are given here: Cngb1 = CNGB1; Gpr98 = USH2C; Grk1 = RHOK; Gucy2e = GUCY2D; Prom1 = PROML1; Rgs9bp = R9AP; Rp1h = RP1; Ush1g = SANS. ‘Known CRE’ indicates the location of published photoreceptor CREs which have experimental support (references are given in MATERIALS AND METHODS). Annotations in this column such as ‘6.5 Kb 5’’ means the tested CRE contained the first 6.5 Kb upstream of the TSS. Known CREs predicted by our algorithm are highlighted in light green. ‘Predicted CRE(s)’ lists candidate CREs predicted by our algorithm which lie within +/− 15 Kb of the TSS. In some cases, two locations are given which represent that CRE prediction closest to the TSS and that with the highest score. Only one location is given when they are the same. Experimentally tested CREs are highlighted in red. The CREs tested for Crx and Elovl4 lie more than 15 Kb downstream of the TSS. The CRE tested for Tulp1 scores below the cutoff threshold of 200. This CRE was selected for testing during the early phases of this project using an earlier version of PhastCons with which it scored above threshold. A third predicted CRE location is given for Opn1mw which corresponds to the locus control region. ‘CRE strength’ indicates the estimated strength of the indicated CRE as tested by electroporation (see Fig. S2). The last four columns of the table show the wild-type-to-mutant ratios of the averaged microarray scores for the given gene. Dark green = downregulated under high stringency (as described in MATERIALS AND METHODS); light green = downregulated under low stringency; red = upregulated under high stringency; orange = upregulated under low stringency. A dash indicates that the gene was not significantly altered in the given mutant. ‘NA’ indicates that this gene is not represented on the Affymetrix Mouse 430 2.0 microarray.
Mentions: Given the remarkable genetic heterogeneity of human retinal disease, we wished to determine the extent to which the causative genes are regulated by Crx, Nrl, and Nr2e3. A set of 58 mouse orthologs of human retinal disease genes from the Retnet database were manually curated (Fig. 2). This set is meant to encompass all disease genes with known or probable photoreceptor-enriched patterns of expression based on analysis of the literature. 89% (50/56) of those disease genes for which microarray data were available were dysregulated to some extent in at least one of the four mutant backgrounds. This finding suggests that the majority of known human retinal disease genes expressed in photoreceptors is under the transcriptional control of Crx, Nrl, and/or Nr2e3.

Bottom Line: Examination of these CREs permitted the definition of a simple cis-regulatory grammar rule associated with high-level expression.When fused to fluorescent reporters, these evolved CREs drove strong, photoreceptor-specific expression in vivo.This study represents the first systematic identification and in vivo validation of CREs in a mammalian neuronal cell type and lays the groundwork for a systems biology of photoreceptor transcriptional regulation.

View Article: PubMed Central - PubMed

Affiliation: Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, United States of America.

ABSTRACT
The photoreceptor cells of the retina are subject to a greater number of genetic diseases than any other cell type in the human body. The majority of more than 120 cloned human blindness genes are highly expressed in photoreceptors. In order to establish an integrative framework in which to understand these diseases, we have undertaken an experimental and computational analysis of the network controlled by the mammalian photoreceptor transcription factors, Crx, Nrl, and Nr2e3. Using microarray and in situ hybridization datasets we have produced a model of this network which contains over 600 genes, including numerous retinal disease loci as well as previously uncharacterized photoreceptor transcription factors. To elucidate the connectivity of this network, we devised a computational algorithm to identify the photoreceptor-specific cis-regulatory elements (CREs) mediating the interactions between these transcription factors and their target genes. In vivo validation of our computational predictions resulted in the discovery of 19 novel photoreceptor-specific CREs near retinal disease genes. Examination of these CREs permitted the definition of a simple cis-regulatory grammar rule associated with high-level expression. To test the generality of this rule, we used an expanded form of it as a selection filter to evolve photoreceptor CREs from random DNA sequences in silico. When fused to fluorescent reporters, these evolved CREs drove strong, photoreceptor-specific expression in vivo. This study represents the first systematic identification and in vivo validation of CREs in a mammalian neuronal cell type and lays the groundwork for a systems biology of photoreceptor transcriptional regulation.

Show MeSH
Related in: MedlinePlus